Spatial variability of soil organic carbon fractions in areas under cultivation of Amazonian species in the southern region of Amazonas state, Brazil

José Igor Silva Praça Igor Silva Praça, Bruna Firmino Enck, Milton Cesar Costa Campos, Marcos Gervasio Pereira, Fernando Gomes Souza, Bruno Campos Mantovanelli, Elilson Gomes Brito Filho, Laercio Santos Silva, Jose Mauricio Cunha


Soil organic carbon (OC) is heterogeneous and sensitive to agricultural management, so knowledge of its spatial variability can improve the monitoring of areas under anthropogenic influence, as OC can serve as a sensitive indicator of changes in the environment. The objective of this study was to evaluate the spatial variability of soil OC fractions in areas of cultivation with Amazonian species in the southern region of Amazonas state. A total of 256 georeferenced data points were collected in the 0.0–0.05 m and 0.05–0.10 m layers in the following agricultural systems: areas with cultivation of Guaraná, Annatto, Cupuaçu and forest. The OC contents were analyzed, and the chemical fractionation of soil organic matter was performed. The analytical results were evaluated through descriptive statistical analysis, and the spatial pattern was evaluated through geostatistical analysis. The conversion of natural ecosystems to agricultural systems affected the rates of addition and decomposition of soil organic matter. Changes in soil organic carbon stocks (SOC stock) due to the uses of different agricultural systems were determined by evaluating the free light fraction of soil organic matter. For the chemical fractions of organic matter, there was a predominance of the humin fraction (C-HU) in relation to the fractions of humic acid (C-FAH), fulvic acid (C-FAF) and OC associated with minerals (COAM) in the different land uses and soil layers analyzed. The geostatistical procedures proved to be important in determining the degree of carbon dependence and its fractionation in the context of spatial variability, and this information is useful in soil quality monitoring.


soil attributes, chemical fractionation, forest, geostatistics, mapping.

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